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ScyllaDB Docs ScyllaDB Open Source Features Change Data Capture (CDC) CDC Stream Generations

CDC Stream Generations¶

Stream IDs used for CDC log entries change over time. A single base partition key might be mapped to one stream in the log today, but to a different stream tomorrow. If you build a query which follows changes made to your favorite partition by using a WHERE clause to specify the proper stream ID, you might need to update the query due to a CDC generation change. The good news is:

stream IDs will only change if you join a new node to the cluster,
it is easy to learn what the used stream IDs are (Querying CDC Streams).

Note

Stream IDs are chosen to maintain the following invariant:

given a base write with partition key pk, the corresponding log table entries will have partition key s_id such that the token of pk is in the same vnode as the token of s_id.

Since adding a node to the cluster splits vnodes into smaller vnodes, we need to (in general) change the used stream IDs.

These sets of stream IDs are called CDC stream generations (also referred to simply as CDC generations).

A CDC generation consists of:

a timestamp, describing the point in time from which this generation starts operating,
a set of stream IDs,
a mapping from the set of tokens (in the entire token ring) to the set of stream IDs in this generation.

This is the mapping used to decide on which stream IDs to use when making writes, as explained in the CDC Streams document. It is a global property of the cluster: it doesn’t depend on the table you’re making writes to.

Caution

The tables mentioned in the following sections: system_distributed.cdc_generation_timestamps and system_distributed.cdc_streams_descriptions_v2 have been introduced in ScyllaDB 4.4. It is highly recommended to upgrade to 4.4 for efficient CDC usage. The last section explains how to run the below examples in ScyllaDB 4.3.

When CDC generations change¶

When you start a fresh cluster, the first generation is created. It has a timestamp chosen using the local clock of the node; it is stored in the time column of the system_distributed.cdc_generation_timestamps table. The stream IDs used in this generation are stored in the streams column of the system_distributed.cdc_streams_descriptions_v2 table. Whenever you bootstrap a new node, you will see a new row appear in cdc_generation_timestamps containing the new generation’s timestamp and a new partition in cdc_streams_descriptions_v2 containing the stream IDs of that new generation.

The cdc_generation_timestamps table is a single-partition table; all timestamps are stored in the key = 'timestamps' partition.

Example: The Next Generation¶

Start a new cluster. Query the cdc_generation_timestamps table to see the available generations:

SELECT time FROM system_distributed.cdc_generation_timestamps WHERE key = 'timestamps';

returns:

 time
---------------------------------
 2020-03-25 12:44:43.006000+0000

(1 rows)

this is the timestamp of the first generation.

Create a table and insert a row:

CREATE TABLE ks.t (pk int, ck int, v int, PRIMARY KEY (pk, ck)) WITH cdc = {'enabled': true};
INSERT INTO ks.t (pk, ck, v) values (0,0,0);

Bootstrap another node. After it finishes joining the cluster, query cdc_generation_timestamps again:

SELECT time FROM system_distributed.cdc_generation_timestamps WHERE key = 'timestamps';

returns:

 time
---------------------------------
 2020-03-25 16:05:29.484000+0000
 2020-03-25 12:44:43.006000+0000

(2 rows)

Note that time is the clustering key column of this table. It is sorted in descending order.

Wait until the new generation starts operating. You can do that by using the CQL now() function to periodically check the current time of the node you’re connected to:
```
SELECT totimestamp(now()) FROM system.local;
```
returns (after waiting):
```
 system.totimestamp(system.now())
----------------------------------
  2020-03-25 16:05:31.939000+0000

(1 rows)
```

Insert a row to your table again:

INSERT INTO ks.t (pk, ck, v) values (0,0,0);

Query the log table:

SELECT "cdc$stream_id", pk FROM ks.t_scylla_cdc_log;

returns:

 cdc$stream_id                      | pk
------------------------------------+----
 0x0521d5ce4a4a8ca552f83d88a1ae55d2 |  0
 0x166eddaa68db9a95af83968998626f7c |  0

(2 rows)

There are two entries with the same base partition key, but in different streams. One of them corresponds to the write made before the generation change, the other — to the write made after the change.

After the operating CDC generation changes, all writes with timestamps greater than or equal to the new generation’s timestamp will use the new stream IDs.

If the clock of the node you’re connected to reports time distant from the write’s timestamp, it may reject the write. If you’ve configured the driver to generate timestamps for you, make sure that the clock of the machine your driver is running on is not too desynchronized with the clock of the node you’re connecting to. That way you can minimize the chance of writes being rejected.

The first generation’s timestamp¶

The first generation’s timestamp is chosen by the first starting node by taking the current time (on the node’s clock) shifted forward by a small duration (around a minute). Therefore you won’t be able to perform writes to CDC-enabled tables immediately after starting the first node: there is no CDC generation operating yet.

Example: “could not find any CDC stream”¶

Suppose a node was started at 17:59:35 UTC+1 time, as reported by the node’s logs:

INFO  2020-02-06 17:59:35,087 [shard 0] init - ScyllaDB version 666.development-0.20200206.9eae0b57a with build-id 052adc1eb0601af2 starting ...

You immediately connected to the node using cqlsh and queried the cdc_generation_timestamps table:

SELECT time FROM system_distributed.cdc_generation_timestamps WHERE key = 'timestamps';

The result was:

 time
---------------------------------
 2020-02-06 17:00:43.100000+0000

(1 rows)

This generation’s timestamp is 17:00:43 UTC time (timestamp columns in ScyllaDB always show the timestamp as a UTC time-date), which is a little more than a minute later compared to the node’s startup time (which was 16:59:35 UTC time).

If you then immediately create a CDC-enabled table and attempt to make an insert:

CREATE KEYSPACE ks WITH replication = {'class':'NetworkTopologyStrategy', 'replication_factor': 3};
CREATE TABLE ks.t (pk int, ck int, v int, PRIMARY KEY (pk, ck)) WITH cdc = {'enabled': true};
INSERT INTO ks.t (pk, ck, v) values (0, 0, 0);

the result will be an error message:

ServerError: cdc::metadata::get_stream: could not find any CDC stream (current time: 2020/02/06 16:59:58). Are we in the middle of a cluster upgrade?

If you see a message like that, it doesn’t necessarily mean something is wrong, as it may simply mean that the first generation hasn’t started operating yet. If you wait for about a minute, you should be able to write to a CDC-enabled table.

You may also see this message if you were running a cluster with an old version of ScyllaDB (which didn’t support CDC) and started a rolling upgrade. Make sure to upgrade all nodes before you start doing CDC writes: one of the nodes will be responsible for creating the first CDC generation and informing other nodes about it.

Differences in ScyllaDB 4.3¶

In ScyllaDB 4.3 the tables cdc_generation_timestamps and cdc_streams_descriptions_v2 don’t exist. Instead there is the cdc_streams_descriptions table. To retrieve all generation timestamps, instead of querying the time column of cdc_generation_timestamps using a single-partition query (i.e. using WHERE key = 'timestamps'), you would query the time column of cdc_streams_descriptions with a full range scan (without specifying a single partition):

SELECT time FROM system_distributed.cdc_streams_descriptions;

Unfortunately, the time column is the partition key column of this table. Therefore the values are not sorted, unlike the values of the time column of the cdc_generation_timestamps table (in which time is the clustering key). You will have to sort them yourselves in order to learn the timestamp of the last generation. Furthermore, querying the table with a full range scan like above requires the coordinator to contact the entire cluster, potentially increasing resource usage and latency. Thus we recommend upgrading to ScyllaDB 4.4 and use the new description tables instead.

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